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TTDFT: A GPU accelerated Tucker tensor DFT code for large-scale Kohn-Sham DFT calculations

Journal Article · · Computer Physics Communications
 [1];  [1]
  1. University of Michigan, Ann Arbor, MI (United States)
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We present the Tucker tensor DFT (TTDFT) code which uses a tensor-structured algorithm with graphic processing unit (GPU) acceleration for conducting ground-state DFT calculations on large-scale systems. The Tucker tensor DFT algorithm uses a localized Tucker tensor basis computed from an additive separable approximation to the Kohn-Sham Hamiltonian. The discrete Kohn-Sham problem is solved using Chebyshev filtered subspace iteration method that relies on matrix-matrix multiplications of a sparse symmetric Hamiltonian matrix and a dense wavefunction matrix, expressed in the localized Tucker tensor basis. These matrix-matrix multiplication operations, which constitute the most computationally intensive step of the solution procedure, are GPU accelerated providing ~8-fold GPU-CPU speedup for these operations on the largest systems studied. In conclusion, the computational performance of the TTDFT code is presented using benchmark studies on aluminum nano-particles and silicon quantum dots with system sizes ranging up to ~7,000 atoms.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); Air Force Office of Scientific Research; Army Research Office; DURIP
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
2424043
Alternate ID(s):
OSTI ID: 1886984
Journal Information:
Computer Physics Communications, Journal Name: Computer Physics Communications Vol. 282; ISSN 0010-4655
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Figures / Tables (10)

Figure 1(p. 7)figure Figure 1
Figure 2(p. 12)figure Figure 2
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Figure 4(p. 13)figure Figure 4
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Table 1(p. 19)table Table 1
Table 2(p. 20)table Table 2
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Related Subjects

97 MATHEMATICS AND COMPUTING
Computer Science
Kohn-Sham density functional theory
L-1 localization
Physics
Real-space
Tensor-structured methods
Tucker tensor